static void CNN(List <DenseVector[]> Data)//畳み込みニューラルネットワーク
{
//MNISTの読み込み
MNistImageLoader imgLoader = MNistImageLoader.Load("train-images.idx3-ubyte");
MNistLabelLoader lLoader = MNistLabelLoader.Load("train-labels.idx1-ubyte");
//////////データ用意
Random rnd = new Random();
List <DenseVector[]> xds = new List <DenseVector[]>();
for (int i = 0; i < 10000000; i++)
{
xds.Add(new DenseVector[2] {
new DenseVector(1), new DenseVector(1)
});
double a = rnd.NextDouble();
xds[i][0][0] = a; xds[i][1][0] = 5 * a * a;
}
List <DenseVector[]> Tests = new List <DenseVector[]>();
for (int i = 0; i < 100; i++)
{
Tests.Add(new DenseVector[2] {
new DenseVector(1), new DenseVector(1)
});
double a = rnd.NextDouble();
Tests[i][0][0] = a; Tests[i][1][0] = a * a;
}
//////////データ用意終
UseNN UseCNN = new UseNN();
UseCNN.Add(new int[] { imgLoader.numberOfRows *imgLoader.numberOfColumns, 100, 100, 100, 100, 100, 100, 20, 20, 9 }
, new int[] { 0, 1, 2, 1, 2, 1, 2, 0, 0, 0 });
}
static void ZikoHugouka(List <DenseVector> Me)
{
UseNN Ziko = new UseNN();
Ziko.Add(new int[] { Me[0].Count, Me[0].Count / 2, Me[0].Count }, new int[] { 0, 0, 0 });
List <DenseVector[]> xds = new List <DenseVector[]>();
for (int i = 0; i < Me.Count; i++)
{
xds.Add(new DenseVector[] { Me[i], Me[i] }); //inputとoutputは同じが理想
}
Ziko.BatchInit(-1, 1); //バッチ処理は利用しない
Ziko.DataInit(xds, xds); //テスト集合と訓練集合は同一
Ziko.NNinit();
Ziko.Train();
}
static void Use()
{
//////////データ用意
Random rnd = new Random();
List <DenseVector[]> xds = new List <DenseVector[]>();
for (int i = 0; i < 1000000; i++)
{
xds.Add(new DenseVector[2] {
new DenseVector(1), new DenseVector(1)
});
double a = rnd.NextDouble();
xds[i][0][0] = a; xds[i][1][0] = a * a;
}
List <DenseVector[]> Tests = new List <DenseVector[]>();
for (int i = 0; i < 100; i++)
{
Tests.Add(new DenseVector[2] {
new DenseVector(1), new DenseVector(1)
});
double a = rnd.NextDouble();
Tests[i][0][0] = a; Tests[i][1][0] = a * a;
}
//////////データ用意終
UseNN test = new UseNN();
test.Add(new int[] { 1, 3, 1 }, new int[] { 0, 0, 0 });
test.BatchInit(10000, 10);
test.DataInit(xds, Tests);
test.NNinit();
test.Train();
test.Test();
Console.ReadLine();
}